From evidence-based policy making to data-driven administration: proposing the data vs. value framework

Abstract

ABSTRACT This study proposes a framework of data-driven administration built on both data and value dimensions and thereby suggests four possible types arising from cases (data-rich and value neutral, data-rich and value-controversial, data-poor and value-neutral, and data-poor and value-controversial). Using an exploratory case study approach, we discuss data-driven administration in the perspective of evidence-based policy-making. Following the tradition of evidence-based policy-making, the advancement of data analytics promotes data-driven administration to solve social problems and innovate government operations. We review relevant cases in Korea and then illustrates how the combinations of two dimensions make practices of data-driven administration successful or not. There is little study pointing out to be mindful of values embedded with social issues in certain domains, even when approached with data-driven administration. The framework of data-driven administration can be used for the better understanding of increasing data analytics practices in the public sector with guiding principles of data readiness and value controversy.